49 citations · 59 across the 27 of their papers we have counts for
28 papers
Simple Features and Honest Calibration for Ambivalence and Hesitancy Recognition in Video
Vikas Kumar, Aditya Mishra, Haroon R. Lone
We address ambivalence and hesitancy (A/H) recognition in the ABAW 2026 BAH Challenge: given a short interview video, predict whether the person shows signs of A/H. Our system comb…
Beyond Benchmarks: Continuous Edge Inference for Fine-Grained Roadside Perception
Aditya Mishra, Haroon Lone
Continuous AI inference on resource-constrained edge hardware introduces deployment effects that are largely invisible to conventional benchmark evaluation, including temporal inst…
Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning
Vedant Waykole, Haroon R. Lone
Federated learning on edge devices must cope with non-IID client data and tight memory budgets. Adaptive optimizers like Adam stabilize training under data heterogeneity but requir…
FedPrism: Adaptive Personalized Federated Learning under Non-IID Data
Prakash Kumbhakar, Shrey Srivastava, Haroon R Lone
Federated Learning (FL) suffers significant performance degradation in real-world deployments characterized by moderate to extreme statistical heterogeneity (non-IID client data).…
CA-AFP: Cluster-Aware Adaptive Federated Pruning
Om Govind Jha, Harsh Shukla, Haroon R. Lone
Federated Learning (FL) faces major challenges in real-world deployments due to statistical heterogeneity across clients and system heterogeneity arising from resource-constrained…
DohaScript: A Large-Scale Multi-Writer Dataset for Continuous Handwritten Hindi Text
Kunwar Arpit Singh, Ankush Prakash, Haroon R Lone
Despite having hundreds of millions of speakers, handwritten Devanagari text remains severely underrepresented in publicly available benchmark datasets. Existing resources are limi…
Evaluating Federated Learning for Cross-Country Mood Inference from Smartphone Sensing Data
Sharmad Kalpande, Saurabh Shirke, Haroon R. Lone
Mood instability is a key behavioral indicator of mental health, yet traditional assessments rely on infrequent and retrospective reports that fail to capture its continuous nature…
DySTAN: Joint Modeling of Sedentary Activity and Social Context from Smartphone Sensors
Aditya Sneh, Nilesh Kumar Sahu, Snehil Gupta +1
Accurately recognizing human context from smartphone sensor data remains a significant challenge, especially in sedentary settings where activities such as studying, attending lect…
A Critical Review of the Need for Knowledge-Centric Evaluation of Quranic Recitation
Mohammed Hilal Al-Kharusi, Khizar Hayat, Khalil Bader Al Ruqeishi +1
The art and science of Quranic recitation (Tajweed), a discipline governed by meticulous phonetic, rhythmic, and theological principles, confronts substantial educational challenge…
Fairness-Aware Few-Shot Learning for Audio-Visual Stress Detection
Anushka Sanjay Shelke, Aditya Sneh, Arya Adyasha +1
Fairness in AI-driven stress detection is critical for equitable mental healthcare, yet existing models frequently exhibit gender bias, particularly in data-scarce scenarios. To ad…
HCFSLN: Adaptive Hyperbolic Few-Shot Learning for Multimodal Anxiety Detection
Aditya Sneh, Nilesh Kumar Sahu, Anushka Sanjay Shelke +2
Anxiety disorders impact millions globally, yet traditional diagnosis relies on clinical interviews, while machine learning models struggle with overfitting due to limited data. La…
Benchmarking Nighttime Traffic Sign Recognition with Illumination-Adaptive Detection and Semantic Attribute Reasoning
Aditya Mishra, Akshay Agarwal, Haroon Lone
Traffic signboards are vital for road safety and intelligent transportation systems. Yet, recognizing traffic signs at night remains underexplored due to the scarcity of real-world…
Real-World Receptivity to Adaptive Mental Health Interventions: Findings from an In-the-Wild Study
Nilesh Kumar Sahu, Aditya Sneh, Snehil Gupta +1
The rise of mobile health (mHealth) technologies has enabled real-time monitoring and intervention for mental health conditions using passively sensed smartphone data. Building on…
RestAware: Non-Invasive Sleep Monitoring Using FMCW Radar and AI-Generated Summaries
Agniva Banerjee, Bhanu Partap Paregi, Haroon R. Lone
Monitoring sleep posture and behavior is critical for diagnosing sleep disorders and improving overall sleep quality. However, traditional approaches, such as wearable devices, cam…
Context-Dependent Autonomic Responses in Social Anxiety During Cognitive-Emotional Stress
Arya Adyasha, Vikas Kumar, Anushka Sanjay Shelke +1
Social anxiety disorder (SAD) is associated with heightened physiological arousal during socially evaluative situations, yet it remains unclear whether similar autonomic responses…
An Offline Mobile Conversational Agent for Mental Health Support: Learning from Emotional Dialogues and Psychological Texts with Student-Centered Evaluation
Vimaleswar A, Prabhu Nandan Sahu, Nilesh Kumar Sahu +1
Mental health plays a crucial role in the overall well-being of an individual. In recent years, digital platforms have increasingly been used to expand mental health and emotional…
RiM: Record, Improve and Maintain Physical Well-being using Federated Learning
Aditya Mishra, Haroon Lone
In academic settings, the demanding environment often forces students to prioritize academic performance over their physical well-being. Moreover, privacy concerns and the inherent…
Are Anxiety Detection Models Generalizable? A Cross-Activity and Cross-Population Study Using Wearables
Nilesh Kumar Sahu, Snehil Gupta, Haroon R Lone
Anxiety-provoking activities, such as public speaking, can trigger heightened anxiety responses in individuals with anxiety disorders. Recent research suggests that physiological s…
AnxietyFaceTrack: A Smartphone-Based Non-Intrusive Approach for Detecting Social Anxiety Using Facial Features
Nilesh Kumar Sahu, Snehil Gupta, Haroon R Lone
Social Anxiety Disorder (SAD) is a widespread mental health condition, yet its lack of objective markers hinders timely detection and intervention. While previous research has focu…
Investigating the Generalizability of ECG Noise Detection Across Diverse Data Sources and Noise Types
Sharmad Kalpande, Nilesh Kumar Sahu, Haroon Lone
Electrocardiograms (ECGs) are vital for monitoring cardiac health, enabling the assessment of heart rate variability (HRV), detection of arrhythmias, and diagnosis of cardiovascula…
Exploring Heart Rate Variability and Heart Rate Dynamics Using Wearables Before, During, and After Speech Activity: Insights from a Controlled Study in a Low-Middle-Income Country
Nilesh Kumar Sahu, Snehil Gupta, Haroon R. Lone
Conventional methods for diagnosing Social Anxiety Disorder (SAD), such as clinical interviews and self-reported questionnaires, often face accessibility barriers and subjective bi…
Beyond Questionnaires: Video Analysis for Social Anxiety Detection
Nilesh Kumar Sahu, Nandigramam Sai Harshit, Rishabh Uikey +1
Social Anxiety Disorder (SAD) significantly impacts individuals' daily lives and relationships. The conventional methods for SAD detection involve physical consultations and self-r…
Thermal Vision: Pioneering Non-Invasive Temperature Tracking in Congested Spaces
Arijit Samal, Haroon R Lone
Non-invasive temperature monitoring of individuals plays a crucial role in identifying and isolating symptomatic individuals. Temperature monitoring becomes particularly vital in s…
Exploring Social Media Posts for Depression Identification: A Study on Reddit Dataset
Nandigramam Sai Harshit, Nilesh Kumar Sahu, Haroon R. Lone
Depression is one of the most common mental disorders affecting an individual's personal and professional life. In this work, we investigated the possibility of utilizing social me…